Restoration of randomly sampled blurred images

Arthur Forman; Abhijit Mahalanobis

doi:10.1117/12.2220828

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12 May 2016 Restoration of randomly sampled blurred images

Arthur Forman, Abhijit Mahalanobis

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Proceedings Volume 9844, Automatic Target Recognition XXVI; 984402 (2016) https://doi.org/10.1117/12.2220828
Event: SPIE Defense + Security, 2016, Baltimore, Maryland, United States

Abstract

The problem this paper addresses is to create an approximation for a source image given only a randomly selected subset of pixel samples extracted from a blurred version of the source image. This problem is different from the conventional image restoration problem, which attempts to create an approximation for the source image given all of the pixel samples available in the blurred image. Our approach finds a minimum weighted L2 norm solution for the ideal image that satisfies linear constraints given by the observed samples of the blurred image.

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Arthur Forman and Abhijit Mahalanobis "Restoration of randomly sampled blurred images", Proc. SPIE 9844, Automatic Target Recognition XXVI, 984402 (12 May 2016); https://doi.org/10.1117/12.2220828

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